A number of radio-based measuring methods are known for the localization of mobile terminal devices such as, for example, smartphones, notebook computers and other mobile communication terminal devices, and these measuring methods can determine the approximate position of a terminal device on the basis of received radio signals. Such methods include localization by a Satellite-Assisted GPS (Global Positioning System) or similar satellite navigation systems. Moreover, signals received in the terminal devices from access points to radio networks can be used for localization purposes. Some methods use the base stations of mobile radio networks as access points. Other methods use radio signals from Wi-Fi or WLAN (Wireless Local Area Network) access points in order to locate terminal devices (the terms Wi-Fi and WLAN are used here synonymously).
In comparison to localization via satellite navigation systems, if there is adequate WLAN coverage of the area where the terminal device that is to be located is present, Wi-Fi-based methods have the advantage that localization is also possible inside buildings, especially department stores, shopping malls, convention centers, airports and the like, where the signals from satellite navigation systems often cannot be received. Moreover, the position of the terminal device, especially in densely built-up areas with poor reception conditions for satellite signals, can often be determined more accurately than with the GPS system, which is currently the only usable satellite navigation system.
The Wi-Fi radio signals used for the localization are, as a rule, so-called beacon signals that are transmitted at regular time intervals by the Wi-Fi access points and that contain an identifier that is unambiguously associated with the access point in question. In this context, this can be a BSSID (Basic Service Set Identification) of the Wi-Fi access point that corresponds to an unambiguous MAC (Media Access Control) address of the access point.
Wi-Fi-based localization methods can be based on lateration. Here, the position of the terminal device is determined as the intersection of three circles in each of whose mid-points there in an access point and whose radii correspond to the distance to the access point. The positions of the access points are determined in advance and they serve as input quantities for the lateration. One way to determine the distances to the access points is offered by the so-called RSS (Received Signal Strength) methods in which the distance to an access point is determined on the basis of the strength of a signal from the access point that has been received by the terminal device, taking into account the transmit power of the access point. With this type of lateration, inaccuracies in the determination of the location arise especially due to the fact that the transmit power of the Wi-Fi access points is generally not precisely known, since not all access points transmit with the same power, and due to the fact that attenuations of the signal caused by objects between the access point and the terminal device are not taken into consideration.
So-called pattern recognition methods can be employed as additional Wi-Fi-based localization methods. The basis of these methods is that a received radio signal pattern containing the signal strengths of the received Wi-Fi signals is compared to reference signal patterns that have been detected in advance. In the case of the pattern recognition methods, the place where the reference pattern having the greatest correspondence with the detected signal pattern was measured is the place that can be assumed as being the position of the terminal device, or else the position is determined on the basis of several reference patterns having a great degree of correspondence as well as on the basis of the associated positions, as a result of which positions of the terminal device between the detection sites of the reference patterns can be determined as locations.
In order to detect the localization information that is used for the Wi-Fi-based localization of terminal devices, measuring drives can be carried out during which measuring vehicles are used to detect the signal strengths of the received signals, the associated identifiers of the Wi-Fi access points as well as the associated positions that can be determined, for example, by GPS. With this approach, which is also known by the term “wardriving”, the reference signal patterns and the associated positions can be detected directly and can be stored in a database that can be accessed in order to determine the positions of terminal devices on the basis of pattern recognition.
Here, however, the drawback arises that the distribution of Wi-Fi access points often changes, especially in densely populated areas with a large number of privately used Wi-Fi access points, since new access points are often installed and existing access points are removed, and the signal propagation for the radio signals from existing access points can also change due to changes in building structures. This calls for frequent measuring drives for data maintenance, and this is very laborious. As a matter of principle, changes that are highly dynamic such as, for example, the switching on and off of access points by their users, cannot be taken into consideration at all by measuring drives. Moreover, other solutions are needed in order to acquire localization information in interior spaces, especially since there are often no positioning systems such as GPS available in such spaces.
The acquisition of the input data for the localization by lateration can be done, for example, manually if operators or users of Wi-Fi access points indicate the position of their access points and their identifiers, which are then stored in a database. Here, the problem exists that the information provided by the users can be inadvertently or intentionally erroneous, and that information about changes in the installation site of an access point, for example, because a user has moved, is often forgotten, thus resulting in an erroneous database. Moreover, even though the detection of changes in the operating state of radio access points is fundamentally possible, in actual practice, this cannot be carried out reliably, since it cannot be ensured that the users will consistently indicate the changes in the operating state.
Furthermore, in order to carry out lateration with high precision, there is a need for precise information about the transmit power of the radio access points. As a rule, however, determining this requires the users to have above-average knowledge about the technology of the radio access points that they use. Consequently, a database that is drawn up on the basis of manual input by users of radio access points generally cannot be augmented with reliable information about the transmit power of the access points taken into account by the database. U.S. Patent Application 2010/0298008 A1 discloses, for example, such above-mentioned techniques for determining the position of mobile stations.